Tradebot was among the first to "co-locate." An excerpt from Scott Patterson's "Dark Pools: High Speed Traders, AI Bandits, and the Threat to the Global Financial System."

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[Editor's Note: Click here to order Dark Pools] Tradebot founder Dave Cummings had more tricks up his sleeve. Around 2004, he began to develop a strategy to make money trading in dark pools, a rising force in the early 2000s. While institutional traders were running from the lit markets, such as Nasdaq (NDAQ), into dark pools, in order to get away from the new breed of high-speed traders, like Tradebot, the speed traders devised methods to swim in the dark as well. Known as "latency arbitrage," the strategy involved gaming the difference between the price of stock in a dark pool and its price in the lit markets, such as Nasdaq and the NYSE (NYX). Tradebot was effectively exploiting the "latency" of the system, a measurement of the time it takes for information to move from place to place in a closed system, such as a market.

Behind the difference: Dark pools that priced stocks based on an electronic feed called the Securities Information Processor, or SIP. If the price of Intel rose to $20.02 from $20 on Nasdaq, many dark pools would get that price through the SIP feed. The trouble with the SIP was that compared to the microsecond speeds of Tradebot's world, it was punishingly slow. For firms practicing latency arb, that amounted to a gold mine. Trades that occurred on Nasdaq would occur a split second before the information reached the dark pools.

Tradebot had a direct line into Nasdaq through its co located ITCH feed, which provided data on the trade before it reached the dark pools. If Intel rose to $20.02 on Nasdaq, Intel would still be trading for $20 on the dark pools. Tradebot could buy up shares of Intel milliseconds before the new price reached the dark pools through the "slow" SIP feed, and then sell Intel for a profit once the new price arrived. As usual with such strategies, the amounts were fleetingly small, just pennies per trade, but done thousands of times a day they could add up significantly.

It was as if most investors were watching the Kentucky Derby on a delayed feed, while Tradebot and high-speed firms like it were at the track and able to make bets all the way to the finish line. The SEC didn't prohibit such trades-in fact, they were seen as making prices more efficient.

But there were already rising signs of trouble. Along with the ascension of the high-octane traders came the dark pools. At first, they were electronic networks that allowed large investors to swap big blocks of stock away from the prying eyes of the lit market. Among the first was a pool called Liquidnet, launched in 2000. In 2004, Dan Mathisson at Credit Suisse built a dark pool called Crossfinder. Pipe- line Trading, founded by a nuclear physicist and a former president of Nasdaq, rolled out a dark pool for big block trading the same year. Goldman Sachs would build a dark pool called Sigma X. Even Getco would eventually launch a dark pool.

As algorithmic trading grew, large investors were finding it harder to trade large chunks of stock. More and more trades were sliced and diced into small, even- numbered pieces-two hundred, three hundred shares-that algos could more easily juggle. The algos deployed complex methods to hunt out the large whale orders the big firms traded, such as "pinging" dark pools with orders that they canceled seconds later. Some used AI pattern-recognition methods to detect their prey. Relatively small at first, the dark pools would grow larger and larger as electronic trading expanded dramatically in the coming years.

The Bots were taking control, pushing their favorite trading networks for more capacity, more speed, more creative ways to make money. The tail was wagging the dog. While plain vanilla mutual fund companies couldn't care less about microsecond quirks in the plumbing of exchanges, high-frequency firms fixated on such information. They designed strategies that required maximum speed, and pushed the electronic networks and exchanges to provide it.

And they did.

"It became about meeting the needs of that specific HFT community," says a technologist who worked for several top ECNs and exchanges in the 2000s. "The game changed. Firms like Getco and Tradebot wanted to know everything about our system so they could manage their orders accordingly. We spent a tremendous amount of money trying to meet their needs. They trained us to be fast. It's all about what functionality can I offer the HFT that they can take ad- vantage of. We're going after guaranteed economics."
High-speed firms worked hand in hand with the trading networks to create exotic order types that would behave in very specific ways. The firms wanted orders that would never go to the NYSE or Nasdaq, or that would only go to other ECNs. Orders that would post a bid or offer, then immediately cancel if they weren't filled.

The electronic traders and the Plumbers who built the pools they swam in didn't see anything wrong with the market they'd help create. They celebrated themselves as democratizers, cracking the insider machine that had picked the pockets of mom and pop for decades. They'd brought light to darkness.

And they were right in many ways. They had defeated their foes. They'd won.

Whether they knew it or not, they were on their way to becoming the new insiders of Wall Street.

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